Hospital-acquired malnutrition: point prevalence, risk identifiers and utility of a digital Dashboard to identify high-risk, long-stay patients in five Australian facilities

J Hum Nutr Diet. 2024 Dec;37(6):1538-1546. doi: 10.1111/jhn.13376. Epub 2024 Oct 1.

Abstract

Background: There are limited hospital-acquired malnutrition (HAM) studies among the plethora of malnutrition literature, and a few studies utilise electronic medical records to assist with malnutrition care. This study therefore aimed to determine the point prevalence of HAM in long-stay adult patients across five facilities, whether any descriptors could assist in identifying these patients and whether a digital Dashboard accurately reflected 'real-time' patient nutritional status.

Methods: HAM was defined as malnutrition first diagnosed >14 days after hospital admission. Eligible patients were consenting adult (≥18 years) inpatients with a length of stay (LOS) >14 days. Palliative, mental health and intensive care patients were excluded. Descriptive, clinical and nutritional data were collected, including nutritional status, and whether a patient had hospital-acquired malnutrition to determine point prevalence. Descriptive Fisher's exact and analysis of variance (ANOVA) tests were used.

Results: Eligible patients (n = 134) were aged 68 ± 16 years, 52% were female and 92% were acute admissions. HAM and malnutrition point prevalence were 4.5% (n = 6/134) and 19% (n = 26/134), respectively. Patients with HAM had 72 days greater LOS than those with malnutrition present on admission (p < 0.001). A high proportion of HAM patients were inpatients at a tertiary facility and longer-stay wards. The Dashboard correctly reflected recent ward dietitian assessments in 94% of patients at one facility (n = 29/31).

Conclusions: HAM point prevalence was 4.5% among adult long-stay patients. Several descriptors may be suitable to screen for at-risk patients in future studies. Digital Dashboards have the potential to explore factors related to HAM.

Keywords: electronic dashboard; electronic medical records; hospital‐acquired malnutrition; malnutrition; point prevalence.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Australia / epidemiology
  • Electronic Health Records / statistics & numerical data
  • Female
  • Hospitalization / statistics & numerical data
  • Humans
  • Inpatients / statistics & numerical data
  • Length of Stay* / statistics & numerical data
  • Male
  • Malnutrition* / diagnosis
  • Malnutrition* / epidemiology
  • Middle Aged
  • Nutrition Assessment*
  • Nutritional Status*
  • Prevalence
  • Risk Factors